MCP server
AI integration for your Promises with MCP
Be ready for agentic commerce. Enable conversational AI agents using LLM to access real-time inventory, delivery promises, and order management through the Model Context Protocol.
Power you integration with OneStock MCP server
Accelerate AI integration
Connect AI partners without technical debt. The Model Context Protocol standard ensures one integration works across multiple AI platforms, eliminating custom API development for each new LLM or agent.
Synchronize data in real time
Ensure inventory levels, delivery promises and order status are always accurate. The MCP server pulls real-time data from OneStock’s unified data layer, building customer trust at every touchpoint.
Scale agentic commerce
Enable AI agents to act as shopping companions across the customer lifecycle—from product discovery and delivery estimation to order modification and returns processing. Support conversational commerce at scale.
Reduce customer service load
Enable customers to resolve queries autonomously through AI interactions. From checking order status to initiating returns, AI agents handle routine tasks that would otherwise require human intervention.
MCP Server Tools
Expose pre-purchase and post-purchase capabilities to AI agents
Conversion-oriented tools
These features help guide shoppers during the buying journey by making product availability and delivery promises transparent. Customers can instantly check inventory levels by SKU, view accurate delivery options and fees, locate nearby stores with opening hours, or even reserve items in-store before picking them up. By removing friction, these tools are aimed at increasing trust and driving sales conversion.
After-sales tools
Once an order is placed, customers often need quick access to order management. This set of tools empowers them to track delivery status in real time, search for orders by various identifiers, cancel an item, update shipping or pickup details, and even initiate returns or exchanges autonomously. These capabilities ensure a smooth and reassuring post-purchase experience, reducing the need for customer service intervention.
Use Cases for MCP
AI-powered shopping assistant
Deploy AI shopping assistants that provide real-time product availability, delivery promises, and personalized recommendations by querying OneStock's unified inventory and delivery promise engine through standardized Model Context Protocol integrations.
Post purchase experience for consumers
Allow customers to track orders, update shipping addresses, cancel items, or initiate returns through natural language conversations with AI agents. Reduce friction and customer service costs while improving satisfaction and order accuracy.
Agentic commerce for luxury retail
Enable personalized, high-touch customer experiences through AI agents that access inventory across boutiques, recommend nearby stores for in-store reservations, and provide accurate delivery promises aligned with luxury service expectations.
Unify customer service data
Aggregate OneStock data via the MCP server and enrich it with third‑party feeds (carriers, marketplaces, CRM, payment platforms) to build a single AI‑ready customer service platform. Reduce manual lookups, cut handling time, and speed dispute resolution.
How It Works
Customer conversation with AI agent
The customer chat with the AI agent asking about product availability, delivery options, order status, or returns.
The LLM identifies the relevant tool
The AI model analyzes the query and selects the appropriate MCP server tool based on contextual descriptions provided by OneStock.
MCP server calls OneStock APIs
The selected tool executes real-time API calls to OneStock’s unified inventory, delivery promise engine, or order management system.
Structured data is returned
OneStock returns accurate, real-time data including stock positions, delivery ETAs with shipping costs, or order tracking details.
AI Agent delivers desponse
The LLM translates structured data into conversational language, providing the customer with actionable information or completing the requested action.
What is the Model Context Protocol (MCP)?
The Model Context Protocol is an open standard for connecting AI applications to external systems. It provides a universal, standardized way for AI agents like Claude or ChatGPT to access data sources, tools, and workflows—similar to how USB-C provides a standardized connection for electronic devices.
Which AI agents support the OneStock MCP server?
Any AI agent that supports the Model Context Protocol can connect to the OneStock MCP server. Anthropic’s Claude and OpenAI’s ChatGPT are among the leading LLM platforms that natively support MCP integrations, enabling seamless access to OneStock retail data.
How does the MCP server improve delivery promise accuracy?
The OneStock MCP server connects directly to OneStock’s delivery promise engine, which calculates ETAs based on real-time stock positions, logistics constraints, carrier routes, preparation times, and capacity management. This ensures delivery promises shown through AI agents are accurate and reliable.
Can customers complete transactions through the MCP server?
The OneStock MCP server currently focuses on providing data visibility and enabling actions like reservations, order modifications, and returns. Full transaction processing (checkout and payment) typically occurs through your existing e-commerce platform, with the AI agent guiding the customer through the process.
Is the OneStock MCP server secure?
Yes. The OneStock MCP server follows industry-standard security practices, including authentication protocols, encrypted data transmission, and role-based access controls. All API calls are authenticated and authorized to ensure data privacy and compliance with GDPR and other regulations.
Discover how Onestock empowers innovation with his MCP server
